Machine Learning Scientist II

Summary

Join Tripadvisor's Machine Learning Team as an ML II Scientist and apply your modeling skills to various problem spaces, including online advertising bidding, customer modeling, and revenue optimization. You will utilize the latest development tools, large datasets, and deploy solutions online to observe real-time impact. This role requires independence, curiosity, and collaboration with a multidisciplinary team. The position offers opportunities to take ownership of projects and identify new applications for machine learning. The location is flexible, offering office, hybrid, or remote options within Portugal. Tripadvisor promotes a culture of personal development with social activities, journal clubs, and industry conference participation.

Requirements

• PhD or Masters in Computer Science, Engineering, Statistics, or related field preferred (or masters with 2+ years of practical experience)
• Knowledge of AB test design and analysis
• Strong background in machine learning and statistics
• Solid foundation on data structures and algorithms
• Proficiency in Python for numerical/statistical programming (our group relies heavily on Numpy/Pandas/Scikit-learn)
• Ability to interpret and write complex SQL queries
• Experience with big data technologies, such as Hive and Spark
• Track record of leading the deployment and maintenance of models

Responsibilities

• Use machine learning models to solve a variety of core business problems across performance marketing
• Seek out new opportunities to apply data science and machine learning in the performance marketing space across all channels (e.g., Web, email, paid marketing)
• Automate ETL pipelines
• Prototype, evaluate, deploy and maintain new models in production
• Design AB tests and analyze their results
• Discover new ways to analyze and interpret the data
• Communicate progress and interpretation of experimental results to technical and business stakeholders

Benefits

• Social activities
• Journal clubs
• Memberships in online learning resources
• Participation in industry conferences
• Remote work